Imaging in a scattering medium relates generally to the methods and techniques for generating an image of the internal properties of a scattering medium based on the detection of scattered energy.
Many systems and techniques have been developed for imaging of scattering media. A typical system for imaging based on scattered energy detection includes a source for directing energy into a target medium and a plurality of detectors for measuring the scattered energy exiting the target medium at various locations with respect to the source. Based on the measured energy exiting the target medium, it is possible to reconstruct an image representation of the cross-sectional scattering, absorption or other properties of the target medium. The values of the absorption and scattering properties of the medium can vary depending on the wavelength and types of energy employed as an imaging source. These values are also frequently spatially varying. These techniques permit the use of types of energy and wavelengths, such as near infrared light energy, that are not suitable for projection imaging techniques, such as x-ray imaging. Thus these techniques have great potential for detecting and imaging properties of media, such as human tissue, that can not be revealed using energy sources commonly employed in projection imaging methods.
Exemplary methods and systems for imaging of scattering media are disclosed in Barbour et al., U.S. Pat. No. 5,137,355, entitled “Method of Imaging a Random Medium,” (hereinafter the “Barbour '355 patent”), Barbour, U.S. Pat. No. 6,081,322, entitled “NIR Clinical Opti-Scan System,” (hereinafter the “Barbour '322 patent”), the Barbour 4147PC1 application, the Barbour 4149PC1 application and the Barbour 4147PC2 application.
As can readily be appreciated, there are many instances where use of these techniques are highly desirable. For example, one flourishing application area is in the field of optical tomography. Optical tomography typically uses near infrared (NIR) energy as an imaging source. Contrary to imaging methods relying on the use of ionizing radiation and/or toxic/radioactive contrast agents, NIR optical tomographic imaging methods bear no risk of causing harm to the patient. The dose of optical intensity used remains far below the threshold of thermal damage and is therefore safe. In the regime of wavelength/intensity/power used, there are no effects on the tissue that accumulate with increasing light energy dose due to over-all irradiation time.
Other favorable attributes of optical tomography include the use of low-cost, potentially portable devices that employ highly integrated, economical off-the-shelf data processing electronics and semiconductor lasers (laser diodes). Such features contrast with other imaging technologies commonly used in clinical diagnosis that require large, fixed facilities such as MRI and x-ray CT imaging. Additionally, since a significant computational effort may be required for both image reconstruction and data analysis, the technology particularly gains from the exponential growth in the ratio of computing power to cost.
It is well appreciated that optical tomography has the potential to provide insights into anatomy and physiology that are unavailable from other imaging methods. For example, optical tomography, using near infrared energy, can identify the spatial variations in blood volume and blood oxygenation levels because of its sensitivity to hemoglobin states. These measures have considerable potential value in diagnosing a broad range of disease processes that are known to influence hemoglobin states.
For example, a common feature of breast tumors, and solid tumors generally, is the occurrence of neovascularized tissue. Ultrastructurally, these tissues are highly disorganized and exhibit functional abnormalities. Often the microvessels are dilated, tortuous, elongated and saccular. There is excessive branching of the vessels, including significant arterio-venous shunting as well as blind vascular endings. Aberrant vascular morphology and decreased vessel density are responsible for increase resistance to flow. The resistance to flow combined with an enlarged diffusion distance, due to the expansion of the extravascular space, can lead to perfusion with hypoxemic and nutrient-deprived blood. The net effect of this state is the occurrence of substantial spatial and temporal heterogeneity in the tumor metabolic microenvironment.
Although these attributes of disease tissue are well appreciated, the availability of a suitable detection methodology able to take full advantage of these characteristics has been notably lacking. An appropriate methodology would be one sensitive not only to altered hemoglobin states (i.e., localized variations in tissue blood volume and oxygenation states), but also to their dynamics under homeostatic conditions or in response to specific provocations.
A variety of methods involving imaging and non-imaging modalities are available for assessing specific features of the vasculature. Detailed images of the vascular architecture involving larger vessels (>1 mm dia.) can be provided using x-ray enhanced contrast imaging or MR angiography. These methods however are insensitive to hemoglobin states and only indirectly provide measures of altered blood flow. The latter is well accomplished, in the case of larger vessels, using Doppler ultrasound, and for near-surface microvessels by laser Doppler measurements, but each is insensitive to variations in tissue blood volume or blood oxygenation. Ultrasound measurements are also limited by their inability to penetrate bone.
In principle, imaging methods based on the detection and analysis of scattered energy, such as optical tomograpic methods, can provide either direct or indirect measures of all of these parameters. However, the known methods and systems have several shortcomings. First, known methods and systems provide images having low contrast and resolution. Second, these methods and systems do not image the dynamic properties of highly scattering media. Third, these methods and systems require accurate calibration and are susceptible to errors. There are several reasons for these problems with known systems and methods. These reasons relate principally to how measurements are performed and how measurement data is analyzed.
For example, when imaging human tissue, the natural occurrence of vascular frequencies arising from cardiac, respiratory and vasomotor activity, produces time variations in, for example, the absorption properties of tissue due to changes in tissue blood volume. Significantly, the process of vasomotion, perfusion first in one region, then another, can be expected to produce spatially convolved images should data be collected on a time frame that is long compared to the reciprocal of the frequency of these processes. Thus methods that collect time-averaged data will predictably yield images whose contrast and resolution are degraded by such variability.
Also influencing the quality of reconstructed images, is the approach used to analyze the acquired data. Many of the known imaging schemes consider, in some manner, the comparison of measured values to predicted values. Typically, these methods, including that described in the Barbour '355 patent, employ numerical methods that seek to minimize the difference between sets of measured and predicted values, and in doing so seek to provide improved estimates of the properties of the unknown target medium. These analysis schemes, referred to as model based methods, assume equivalency in the efficiency of measured detector values and computed predicted values. Although the derivation of accurate estimates of the efficiency of measured responses is possible in principle, in practice, the natural plasticity of tissue, its mainly arbitrary shape and variable composition and noted variability in hemoglobin levels, all serve to confound efforts to devise practical methods that provide reliable estimates.
In addition, the physics of light transport in highly scattering media, such as tissue, imposes further practical constraints that relate to the method adopted for data analysis. At issue is the required accuracy of assumptions made in order to generate predicted detector values, especially those adopted for the initial estimate. These assumptions are commonly referred to as the “initial guess”. Small errors in the initial guess of optical properties of the reference medium can lead to large errors in the computed detector values. One consequence of this can be the severe corruption of the information content of the data vectors leading to artifact-laden images. Adding to the mentioned uncertainties is the well-known property of reconstruction methods that employ linear operators regarding their sensitivity to undetermined data sets (i.e., insufficient amount of collected data) and measurements based on restricted views (e.g., backscatter only, transmission only). The net effect of these limitations can render solutions to image recovery problems of this type overly sensitive to the influence of experimental noise (i.e., ill-conditioned), provide nonunique solutions (ill-posed) or both.
These concerns are well appreciated by those skilled in the art of image reconstruction methods. It is also well appreciated that, in general, there are no simple or well-defined methods that can be universally applied to overcome the noted limitations. In this regard, specification of suitable conditions that can satisfactorily deal with the noted concerns is an art whose successful implementation requires considerable skill.
In addition to the need to provide stable solutions to the image reconstruction problem, consideration of the information content of the reconstructed image has considerable importance. As presently practiced, the method of optical tomography considers the evaluation of static states or employs time averaging methods to minimize the influence of signal instability originating from tissue dynamics.
The goal of these studies is to provide image maps that define spatial variations in the optical properties of tissue (usually, absorption and scatter) from which may be derived, for instance, estimates of spatial varying hemoglobin states. It is understood however, that the latter is fundamentally governed by dynamic processes whose details have the potential to reveal a wealth of information regarding functional features of the vasculature, in particular as it relates to its interaction with surrounding tissue.
The ability to measure dynamic processes of a medium can reveal information that is unobservable from static or time-averaged measures. In the case of physiological systems, the form of the dynamic process has added significance. For instance, it is well understood that many time varying processing have an underlying nonlinear character. Nonlinear dynamic processes, in biological systems, are often chaotic and exhibit the characteristic feature of sensitivity to initial conditions.
The existence of such behavior has important implications in the understanding of disease processes and well as for the approaches taken for therapy. For instance, the approach needed to control a chaotic system is quite different from that for a linear system, wherein the system response is proportional to the magnitude of the input stimulus. Thus it has been proposed that more effective therapies can be realized from a series of well-timed perturbations rather than from the standard approach of applying a constant stimulus, the method commonly used in many pharmacological interventions. Also of interest, and related to this, is the seemingly general finding that the occurrence of chaotic behavior in physiological systems is a sign of health and its absence is a sign of disease.
For instance, it is known that heart rate variability is chaotic. Significantly, loss of this signature with the appearance of periodic oscillations is among the strongest predictors of sudden cardiac death. A similar phenomenology has been observed in infants who succumb to sudden infant death syndrome. In this case, the normally chaotic respiratory rate becomes periodic prior to the fatal incident. Similarly, during epileptic seizures, electroencephalographic recordings exhibit a transition from chaotic to periodic activity.
Presently, the capacity to monitor dynamic behavior in vascular structures is limited principally to near surface measures using laser Doppler methods. Measures of the time variability of the vascular caliber and flow motion for larger vessels is possible using Duplex ultrasound. However, these measures are insensitive to the activity of the microvasculature, do not provide for full cross-sectional views, and are not sensitive to the dynamics of hemoglobin states.
Although optical methods, such as Laser Doppler, pulse oximetry, photoplethysmography and the like, can be used to monitor dynamic states of the vasulature, none are capable of providing such measures in the form of a cross-sectional image, especially in the case of large tissue structures. Moreover, known optical methods for cross-sectional imaging of the properties of a scattering media have not been used to derive dynamic measures of these states, and are plagued with a host of technical limitations, such as low contrast, low resolution images, prolonged computing times, excessive sensitivity to errors in initial estimates. These limitations render it unlikely that useful information regarding dynamic states could be derived from these known methods.
Overcoming the indicated drawbacks and concerns is critical for widespread practical implementation of optical tomography as a diagnostic tool because (1) improved contrast and resolution are essential to feature identification and visualization, (2) a static (snapshot) or time averaged image of a time evolving property does not provide discovery of the physiological dynamic processes and (3) measures of dynamic processes can yield critical information needed for improved diagnostic methods and therapies.
For the foregoing reasons, there is a need for a method of improving the contrast and resolution of reconstructed images. There is also a need for a method of imaging dynamic properties of dense scattering media, especially as it relates to dynamic properties of vascular states in large tissue structures as revealed by time variation in hemoglobin states. There is yet a further need for a method that can provide dynamic images without undue reliance on complex calibration schemes or computationally intensive numerical methods.